Reputation: 25
I have some data in a CSV that is formatted as such (I deleted some columns for simplicity):
Year,Region,Round,Diff
2014,South,Second Round,-24
2015,West,First Round,48
# ...lots of rows of this
I want to use both the string data in the Region
and Round
columns and the integer data in the Diff
column.
Here is my relevant code:
import sklearn
import numpy as np
from numpy import genfromtxt
from StringIO import StringIO
# Some other code...
my_dtype=[('Year', int), ('Region', str),('Round', str),('Diff', int)]
data = np.genfromtxt(my_file, delimiter=',',names=True,dtype=my_dtype)
print data
When I print my data, I get the following. NumPy is making every string an empty string.
[ ( 2014, '', '', -24)
( 2010, '', '', 48)
...]
Does anyone know how I could fix this? Am I using the dtype attribute wrong? Or something else? Thanks in advance.
Upvotes: 0
Views: 49
Reputation: 114811
Instead of putting str
for the data type of the text fields, use the S
format with a maximum string length:
In [10]: my_dtype = [('Year', int), ('Region', 'S8'), ('Round', 'S16'), ('Diff', int)]
In [11]: data = np.genfromtxt('regions.csv', delimiter=',', names=True, dtype=my_dtype)
In [12]: data
Out[12]:
array([(2014, b'South', b'Second Round', -24),
(2015, b'West', b'First Round', 48)],
dtype=[('Year', '<i8'), ('Region', 'S8'), ('Round', 'S16'), ('Diff', '<i8')])
You can also use dtype=None
and let genfromtxt()
determine the data type for you:
In [13]: data = np.genfromtxt('regions.csv', delimiter=',', names=True, dtype=None)
In [14]: data
Out[14]:
array([(2014, b'South', b'Second Round', -24),
(2015, b'West', b'First Round', 48)],
dtype=[('Year', '<i8'), ('Region', 'S5'), ('Round', 'S12'), ('Diff', '<i8')])
Upvotes: 1